In ropenscilabs/pkginspector: Package review tools

library(knitr)
library(dplyr)
opts_chunk$set(echo = TRUE)
library(desc)
library(fs)
library(cloc)
library(spelling)
library(goodpractice)
library(covr)
library(purrr)
library(DT)
library(formattable)
library(pkgreviewr)

Sys.setlocale("LC_COLLATE", "C")
Sys.setenv("_R_CHECK_TIMINGS_"=0, "_R_CHECK_LENGTH_1_CONDITION_" = TRUE)

pkgdesc <- desc(path(params$pkgdir, "DESCRIPTION"))
pkgname <- pkgdesc$get_field("Package")

r paste('Onboarding Submission Report: ', pkgname) {.tabset}

README

# if (file_exists(path(params$pkgdir, "README.md")))  {
#   #knit_print(asis_output(paste(readLines(path(params$pkgdir, "README.md")), collapse = "\n")))
#   readme_tmp <- tempfile()
#   rmarkdown::pandoc_convert(path(params$pkgdir, "README.md"), to="html",
#                                output = readme_tmp)
#   knit_print(asis_output(
#     paste(readLines(readme_tmp), collapse="\n")
#   ))
# } else if (length(dir_ls(params$pkgdir, regexp = "README", ignore.case = TRUE))) {
#   cat(readLines(dir_ls(params$pkgdir, regexp = "README", ignore.case = TRUE)[1]), sep = "\n")
# } else {
#   knit_print(asis_output('<span style="color: red;"><strong>No README found!<strong/><span/>'))
# }

DESCRIPTION

pkgdesc

R CMD check

gp_obj <- safely(quietly(gp))(path = params$pkgdir)

if(is.null(gp_obj$error)) {
  cat(paste(
    gp_obj$result$result$rcmdcheck$output$stdout,
    "\n----------\n",
    gp_obj$result$result$rcmdcheck$outstdout),
    "\n",
    "Session info \n",
    paste(gp_obj$result$result$rcmdcheck$package, gp_obj$result$result$rcmdcheck$version),
    "\n",
    paste("R version:", gp_obj$result$result$rcmdcheck$rversion),
    "\n",
    paste("Platform:", gp_obj$result$result$rcmdcheck$platform))
}

goodpractice

if(!is.null(gp_obj$error)) {
  stop(gp_obj$error)
}
if(!is.null(gp_obj$results$warnings)) {
  warning(gp_obj$result$warnings)
}

gp_obj$result$result

Spelling

spell_obj <- spell_check_package(params$pkgdir)
spell_obj

Tests

TODO: Better way to explore test results?

test_obj <- quietly(devtools::test)(params$pkgdir, reporter = testthat::SummaryReporter)

fail_fmt <- formatter("span",
                      style = x ~ formattable::style("display" = "block", "padding" = "0 4px", "border-radius" = "4px",  "background-color" = ifelse(x, "lightpink", "white")))
skip_fmt <- formatter("span",
                      style = x ~ formattable::style("display" = "block", "padding" = "0 4px", "border-radius" = "4px",  "background-color" = ifelse(x, "yellow", "white")))

as.data.frame(test_obj$result) %>%
  mutate_at(vars(failed, skipped, error, warning), as.logical) %>%
  arrange(desc(failed), desc(error), desc(warning), desc(skipped)) %>% formattable(list(
  error = fail_fmt,
  skipped = skip_fmt,
  warning = fail_fmt,
  failed = fail_fmt
)) %>%
as.datatable(rownames=FALSE, autoHideNavigation = TRUE, width = "100%")

Test Coverage

TODO: Cleanup the widget for this and make in a function in the package

# source("/home/rstudio/coverage-report-widget.R")
# if(!is.null(gp_obj$result)) {
# covr_report <- report_widget(gp_obj$result$result$covr$coverage)
# covr_report
# }

Dependencies

TODO: Show package dependency tree. Best option is currently r-lib/pkgdepenends, but current version broken, so using old commit.

# 
# pkgdepends_obj <- pkgdepends::remotes$new(paste0("installed::",
#                                     system.file(package=pkgname)),
#                             lib = tempfile())
# pkgdepends_obj$solve()
# pkgdepends_obj$draw_tree()

Functions Calls

## get summary of function calls and signature
res <- pkgreviewr::rev_fn_summary(params$pkgdir)

DT::datatable(res)

Argument defaults

Are the default arguments consistent across all the functions? Here we check so across all functions (exported and non-exported):

DT::datatable(pkgreviewr::rev_args(params$pkgdir)$arg_df)

The following plot visualizes which arguments are used in which functions.

corrplot::corrplot(pkgreviewr::rev_args(params$pkgdir)$arg_map, method = 'square', cl.pos = "n")

You can also apply pkgreviewr::rev_args() to the subset of exported functions. The function also returns a logical matrix with the functions in the rows and the arguments in the columns to identify where each argument is used.

Dependency usage

rev_dependency_usage()

CLOC

TODO: Why are there no results when knitting here?

cloc_obj <- cloc::cloc(params$pkgdir)

cloc_obj %>%
  mutate_at(vars(ends_with("pct")),
            funs(as.character(formattable::percent(., digits=1)))) %>%
  select(-source) %>%
  DT::datatable(rownames = FALSE, width= "100%",  autoHideNavigation=TRUE)

Functions / Help Topics

TODOs

• Table of functions with
  • name
  • signature
  • short help topic description
  • cyclomatic complexity
  • lines of code
  • some measure of network importance (how many fns depend on it, how many package fns it calls (resursively))
• Network of function dependencies
  • use igraph.from.graphNEL(makeCallGraph(as.list(getNamespace(pkgname)))), networkD3?, visNetwork
  • distinguish exported/internal functions
• Some way to detect/show S3, S4, R6 usage?
• Package PDF manual

if(!is.null(gp_obj$result)) {
  kable(gp_obj$result$result$cyclocomp, row.names = FALSE)
}

Package Dependancies

# Plan here is to render the manual and store it as a downloadable base64 object)
# mp <- tempdir()
# devtools::build_manual(pkg = params$pkgdir, path = mp)
# list.files(mp)

ropenscilabs/pkginspector documentation built on May 15, 2022, 5:30 a.m.